文章基本信息

标题：Fault Diagnostic System Bearing Centrifugal Pump Using K-Means Method For Thermography Image And Signal Analysis Vibrations
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作者：Agung Yudhistira Hidayat ; Achmad Widodo ; Gunawan Dwi Haryadi 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2018
卷号：159
DOI：10.1051/matecconf/201815901013
语种：English
出版社：EDP Sciences
摘要：Numerous studies reported that infrared thermography and vibration are condition monitoring technology that is important and effective for doing a condition diagnostic of bearing centrifugal pump health without destructing or disturbing machine operational. This paper focuses on thermography image processing based on K-Mean color segmentation which will produce normal and abnormal condition features. Health diagnostic of bearing by processing of digital image, image clustering, segmentation and extraction. Extraction of image pattern is done by calculating the area of heat point and color feature bearing condition of RGB colour space and active contour segmentation in order to process and differentiate between normal and abnormal bearing image by statistical technique. The parameters that can be used as reference to classifying conditions are standard deviation, Mean, Variance, Skewness, Kurtosis, Vibration (RMS) and Shape features (area). Final step is determining the boundary condition between normal and abnormal using statistical logic method.